Attenuated Total Reflection Fourier Transform Infrared Spectroscopy for Forensic Screening of Long-Term Alcohol Consumption from Human Nails

Fourier transform infrared (FT-IR) spectroscopy is usedthroughoutforensic laboratories for many applications. FT-IR spectroscopy canbe useful with ATR accessories in forensic analysis for several reasons.It provides excellent data quality combined with high reproducibility,with minimal user-induced variations and no sample preparation. Spectrafrom heterogeneous biological systems, including the integumentarysystem, can be associated with hundreds or thousands of biomolecules.The nail matrix of keratin possesses a complicated structure withcaptured circulating metabolites whose presence may vary in spaceand time depending on context and history. We developed a new approachby using machine-learning (ML) tools to leverage the potential andenhance the selectivity of the instrument, create classification models,and provide invaluable information saved in human nails with statisticalconfidence. Here, we report chemometric analysis of ATR FT-IR spectrafor the classification and prediction of long-term alcohol consumptionfrom nail clippings in 63 donors. A partial least squares discriminantanalysis (PLS-DA) was used to create a classification model that wasvalidated against an independent data set which resulted in 91% correctlyclassified spectra. However, when considering the prediction resultsat the donor level, 100% accuracy was achieved, and all donors werecorrectly classified. To the best of our knowledge, this proof-of-conceptstudy demonstrates for the first time the ability of ATR FT-IR spectroscopyto discriminate donors who do not drink alcohol from those who drinkalcohol on a regular basis.